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Dubravka Svetina Valdivia; Shenghai Dai – Journal of Experimental Education, 2024
Applications of polytomous IRT models in applied fields (e.g., health, education, psychology) are abound. However, little is known about the impact of the number of categories and sample size requirements for precise parameter recovery. In a simulation study, we investigated the impact of the number of response categories and required sample size…
Descriptors: Item Response Theory, Sample Size, Models, Classification
Wang, Jue; Engelhard, George; Combs, Trenton – Journal of Experimental Education, 2023
Unfolding models are frequently used to develop scales for measuring attitudes. Recently, unfolding models have been applied to examine rater severity and accuracy within the context of rater-mediated assessments. One of the problems in applying unfolding models to rater-mediated assessments is that the substantive interpretations of the latent…
Descriptors: Writing Evaluation, Scoring, Accuracy, Computational Linguistics
Fong, Carlton J.; Lee, Jihyun; Krou, Megan R.; Hoff, Meagan A.; Johnston-Ashton, Karen; Gonzales, Cassandra; Beretvas, S. Natasha – Journal of Experimental Education, 2023
The Learning and Study Strategies Inventory (LASSI; Weinstein et al., "Learning and study strategies inventory." H&H Publishing, 1987) is a prominent instrument used in thousands of institutions worldwide as an educational and research tool. Despite its widespread prevalence, there are inconsistencies regarding the underlying latent…
Descriptors: Meta Analysis, Factor Structure, Learning Strategies, Measures (Individuals)
Fay, Derek M.; Levy, Roy; Schulte, Ann C. – Journal of Experimental Education, 2022
Longitudinal data structures are frequently encountered in a variety of disciplines in the social and behavioral sciences. Growth curve modeling offers a highly extensible framework that allows for the exploration of rich hypotheses. However, owing to the presence of interrelated sources of potential data-model misfit at multiple levels, the…
Descriptors: Measurement, Models, Bayesian Statistics, Hierarchical Linear Modeling
Schweizer, Karl; Wang, Tengfei; Ren, Xuezhu – Journal of Experimental Education, 2022
The essay reports two studies on confirmatory factor analysis of speeded data with an effect of selective responding. This response strategy leads test takers to choose their own working order instead of completing the items along with the given order. Methods for detecting speededness despite such a deviation from the given order are proposed and…
Descriptors: Factor Analysis, Response Style (Tests), Decision Making, Test Items
Gill, M. G.; Trevors, G.; Greene, J. A.; Algina, J. – Journal of Experimental Education, 2022
The overall purpose of this study was to investigate the role of personal relevance in conceptual change. First, we used an experimental design to investigate the role of augmented activation--which directly implicated teachers' personal prior beliefs about mathematics learning and instruction--and refutational text manipulations on short and…
Descriptors: Preservice Teachers, Mathematics Teachers, Teacher Attitudes, Beliefs
Aloe, Ariel M.; Thompson, Christopher G.; Liu, Zhijiang; Lin, Lifeng – Journal of Experimental Education, 2022
The distribution of the standardized mean difference is well understood. However, in many situations, researchers need to estimate an effect size to represent the relationship between a continuous outcome and a dichotomous grouping variable, adjusting for the effect of a covariate (or a set of covariates). Typically, this adjustment takes place…
Descriptors: Effect Size, Meta Analysis, Quasiexperimental Design, Regression (Statistics)
Shero, Jeffrey A.; Al Otaiba, Stephanie; Schatschneider, Chris; Hart, Sara A. – Journal of Experimental Education, 2022
Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…
Descriptors: Data Analysis, Educational Research, Nonparametric Statistics, Efficiency
Aidoo, Eric Nimako; Appiah, Simon K.; Boateng, Alexander – Journal of Experimental Education, 2021
This study investigated the small sample biasness of the ordered logit model parameters under multicollinearity using Monte Carlo simulation. The results showed that the level of biasness associated with the ordered logit model parameters consistently decreases for an increasing sample size while the distribution of the parameters becomes less…
Descriptors: Statistical Bias, Monte Carlo Methods, Simulation, Sample Size
Flunger, Barbara; Trautwein, Ulrich; Nagengast, Benjamin; Lüdtke, Oliver; Niggli, Alois; Schnyder, Inge – Journal of Experimental Education, 2021
The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…
Descriptors: Foreign Countries, Middle School Students, Grade 8, Multivariate Analysis
Lee, Young Ri; Hong, Sehee – Journal of Experimental Education, 2019
The present study examines bias in parameter estimates and standard error in cross-classified random effect modeling (CCREM) caused by omitting the random interaction effects of the cross-classified factors, focusing on the effect of a sample size within cells and ratio of a small cell. A Monte Carlo simulation study was conducted to compare the…
Descriptors: Interaction, Models, Sample Size, Monte Carlo Methods
McNeish, Daniel – Journal of Experimental Education, 2018
Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…
Descriptors: Measures (Individuals), Nonparametric Statistics, Item Response Theory, Regression (Statistics)
Ning, Ling; Luo, Wen – Journal of Experimental Education, 2018
Piecewise GMM with unknown turning points is a new procedure to investigate heterogeneous subpopulations' growth trajectories consisting of distinct developmental phases. Unlike the conventional PGMM, which relies on theory or experiment design to specify turning points a priori, the new procedure allows for an optimal location of turning points…
Descriptors: Statistical Analysis, Models, Classification, Comparative Analysis
Acee, Taylor W.; Weinstein, Claire Ellen; Hoang, Theresa V.; Flaggs, Darolyn A. – Journal of Experimental Education, 2018
We discuss task-value interventions as one type of relevance intervention and propose a process model of value reappraisal whereby task-value interventions elicit cognitive-affective responses that lead to attitude change and in turn affect academic outcomes. The model incorporates a metacognitive component showing that students can intentionally…
Descriptors: Models, Reflection, Intervention, Academic Achievement
Priniski, Stacy J.; Hecht, Cameron A.; Harackiewicz, Judith M. – Journal of Experimental Education, 2018
Personal relevance goes by many names in the motivation literature, stemming from a number of theoretical frameworks. Currently these lines of research are being conducted in parallel with little synthesis across them, perhaps because there is no unifying definition of the relevance construct within which this research can be situated. In this…
Descriptors: Relevance (Education), Models, Student Interests, Expectation